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Ensemble Methods for Multilayer Feedforward

机译:多层前馈的合奏方法

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摘要

Training an ensemble of networks is an interesting way to improve the performance with respect to a single network. However there are several method to construct the ensemble and there are no results showing which one could be the most appropriate. In this paper we present a comparison of eleven different method. We have trained ensembles of a reduced number of networks (3 and 9) because in this case the computational cost is not high and the method is suitable for applications. The results show that the improvement in performance from three to nine networks is marginal. Also the improvement of performance of the different methods with respect to a simple ensemble is usually less than 1%.
机译:训练一组网络是一种提高单个网络性能的有趣方法。但是,有几种方法可以构建整体,而没有结果表明哪种方法最合适。在本文中,我们对11种不同方法进行了比较。我们已经训练了数量较少的网络(3和9)的集成体,因为在这种情况下计算成本不高,并且该方法适合于应用。结果表明,从三个网络到九个网络的性能提升是微不足道的。而且,相对于简单的合奏,不同方法的性能改进通常小于1%。

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